Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "139" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 33 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460016 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.206526 | 1.606748 | 1.038740 | -1.048854 | 0.274315 | -0.884086 | -1.739684 | -0.356164 | 0.5738 | 0.5678 | 0.3363 | nan | nan |
| 2460015 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.262247 | 1.616077 | 1.114792 | -1.083136 | 0.176276 | -0.881849 | -0.913305 | 0.083715 | 0.5843 | 0.5746 | 0.3361 | nan | nan |
| 2460014 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.984681 | 2.233705 | 0.859170 | -1.066453 | -0.331784 | -0.266779 | -0.105456 | 0.367360 | 0.5551 | 0.5467 | 0.3391 | nan | nan |
| 2460013 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.257821 | 1.924904 | 1.153038 | -0.958187 | 0.490458 | -0.665590 | -1.493888 | 0.287320 | 0.5774 | 0.5761 | 0.3408 | nan | nan |
| 2460012 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.201351 | 1.595928 | 0.987809 | -1.076697 | 0.501616 | -0.867209 | -1.913060 | 0.585422 | 0.5640 | 0.5591 | 0.3486 | nan | nan |
| 2460011 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.627420 | 1.563619 | 1.582888 | -1.330092 | 1.786612 | -0.307521 | -1.646835 | -0.190701 | 0.5821 | 0.5793 | 0.3542 | nan | nan |
| 2460010 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.925354 | 0.117805 | 1.795583 | -0.961552 | 1.047707 | -1.536251 | -1.020665 | 0.835952 | 0.5916 | 0.5959 | 0.3615 | nan | nan |
| 2460009 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.659488 | -0.219055 | 1.521613 | -1.322096 | 0.958142 | -0.858399 | -1.460041 | 0.910000 | 0.5955 | 0.6038 | 0.3660 | nan | nan |
| 2460008 | RF_maintenance | 100.00% | 0.00% | 1.03% | 0.00% | - | - | 2.279673 | -0.057864 | 1.828603 | -1.607545 | 0.919097 | 16.454656 | 0.399431 | 1.964236 | 0.6312 | 0.6160 | 0.3288 | nan | nan |
| 2460007 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.093423 | 1.277197 | 1.256811 | -1.266976 | 0.207992 | -0.867891 | -1.697641 | -0.816002 | 0.6016 | 0.6022 | 0.3465 | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 99.00% | 99.08% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.2845 | 0.2745 | 0.1616 | nan | nan |
| 2459998 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.197555 | 1.342728 | 1.186868 | -0.941130 | 0.421022 | -0.359026 | -1.847791 | -0.492085 | 0.6007 | 0.6017 | 0.3655 | nan | nan |
| 2459997 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459996 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.895669 | 1.461300 | 1.385825 | -1.143269 | 0.669931 | -0.757478 | -1.227795 | 0.227342 | 0.6245 | 0.6266 | 0.3767 | nan | nan |
| 2459995 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.666108 | 1.532931 | 1.473621 | -1.148881 | 0.822231 | -0.398544 | -0.335904 | 0.703216 | 0.6036 | 0.6048 | 0.3790 | nan | nan |
| 2459994 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.331711 | 1.511766 | 1.416321 | -1.067755 | 0.611539 | -0.284747 | -0.171244 | 0.601544 | 0.5980 | 0.5963 | 0.3770 | nan | nan |
| 2459993 | RF_maintenance | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 238.758406 | 237.840226 | inf | inf | 2730.096528 | 2728.831814 | 4589.313071 | 4566.236430 | nan | nan | nan | nan | nan |
| 2459991 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.511850 | 1.973235 | 1.613324 | -0.857397 | 1.225660 | -0.345117 | -0.670859 | -0.115464 | 0.6196 | 0.6115 | 0.3737 | nan | nan |
| 2459990 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.238969 | 1.803647 | 1.637512 | -0.722851 | 1.051709 | -0.308176 | -0.744491 | -0.064354 | 0.6160 | 0.6097 | 0.3704 | nan | nan |
| 2459989 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.315958 | 1.855521 | 1.675523 | -0.706278 | 0.742214 | -0.822732 | -0.922747 | -0.178496 | 0.6092 | 0.6054 | 0.3713 | nan | nan |
| 2459988 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.538032 | 2.133065 | 1.640840 | -0.805840 | 0.923125 | -0.431909 | -0.004366 | 0.294476 | 0.6097 | 0.6085 | 0.3657 | nan | nan |
| 2459987 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.333949 | 1.417755 | 1.447912 | -1.085154 | -0.081421 | -0.355512 | -1.942236 | -1.010282 | 0.6205 | 0.6163 | 0.3631 | nan | nan |
| 2459986 | RF_maintenance | 100.00% | 0.00% | 0.00% | 0.00% | - | - | 1.556257 | 1.814030 | 1.595988 | -1.023002 | 0.654999 | 6.808308 | 0.614950 | 14.006658 | 0.6356 | 0.6341 | 0.3275 | nan | nan |
| 2459985 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.534989 | 1.500301 | 1.336053 | -0.833124 | 0.238524 | -1.167339 | -0.619552 | 0.179973 | 0.6184 | 0.6156 | 0.3718 | nan | nan |
| 2459984 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.782731 | 1.551550 | 1.414890 | -0.832248 | 0.941467 | -0.589018 | -0.745238 | -0.518754 | 0.6310 | 0.6323 | 0.3507 | nan | nan |
| 2459983 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.114408 | -0.176024 | 1.470231 | -0.839423 | 0.808179 | -0.438120 | -0.368120 | -0.428077 | 0.6416 | 0.6611 | 0.3155 | nan | nan |
| 2459982 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.677168 | 0.602346 | 0.839678 | -1.137902 | -0.878253 | -0.930533 | -0.281767 | -1.426429 | 0.6832 | 0.6873 | 0.2881 | nan | nan |
| 2459981 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.822945 | 0.024241 | 1.785473 | -0.730061 | 1.195661 | -1.083848 | -0.365829 | 0.302942 | 0.6181 | 0.6227 | 0.3703 | nan | nan |
| 2459980 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.673381 | -0.155047 | 1.287751 | -1.154340 | 0.352244 | -1.439508 | 0.726614 | -1.506787 | 0.6556 | 0.6636 | 0.3043 | nan | nan |
| 2459979 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.726490 | -0.141128 | 1.384920 | -1.029709 | 0.695672 | -1.397232 | -1.231275 | -0.288140 | 0.6114 | 0.6191 | 0.3716 | nan | nan |
| 2459978 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.777718 | -0.074015 | 1.595547 | -0.915646 | 0.723953 | -1.100068 | -0.928032 | -0.174244 | 0.6115 | 0.6186 | 0.3782 | nan | nan |
| 2459977 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 1.139508 | -0.072078 | 1.295252 | -1.051462 | 0.629719 | -1.384103 | -1.145565 | 0.064470 | 0.5757 | 0.5845 | 0.3385 | nan | nan |
| 2459976 | RF_maintenance | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.909939 | -0.058542 | 1.467250 | -1.012742 | 0.912279 | -1.028725 | -0.712418 | -0.094504 | 0.6159 | 0.6227 | 0.3715 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.606748 | 1.606748 | 1.206526 | -1.048854 | 1.038740 | -0.884086 | 0.274315 | -0.356164 | -1.739684 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.616077 | 1.616077 | 1.262247 | -1.083136 | 1.114792 | -0.881849 | 0.176276 | 0.083715 | -0.913305 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 2.233705 | 0.984681 | 2.233705 | 0.859170 | -1.066453 | -0.331784 | -0.266779 | -0.105456 | 0.367360 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.924904 | 1.257821 | 1.924904 | 1.153038 | -0.958187 | 0.490458 | -0.665590 | -1.493888 | 0.287320 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.595928 | 1.201351 | 1.595928 | 0.987809 | -1.076697 | 0.501616 | -0.867209 | -1.913060 | 0.585422 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Temporal Variability | 1.786612 | 1.627420 | 1.563619 | 1.582888 | -1.330092 | 1.786612 | -0.307521 | -1.646835 | -0.190701 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | 1.925354 | 1.925354 | 0.117805 | 1.795583 | -0.961552 | 1.047707 | -1.536251 | -1.020665 | 0.835952 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | 1.659488 | 1.659488 | -0.219055 | 1.521613 | -1.322096 | 0.958142 | -0.858399 | -1.460041 | 0.910000 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Temporal Variability | 16.454656 | -0.057864 | 2.279673 | -1.607545 | 1.828603 | 16.454656 | 0.919097 | 1.964236 | 0.399431 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.277197 | 1.093423 | 1.277197 | 1.256811 | -1.266976 | 0.207992 | -0.867891 | -1.697641 | -0.816002 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.342728 | 1.197555 | 1.342728 | 1.186868 | -0.941130 | 0.421022 | -0.359026 | -1.847791 | -0.492085 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | 1.895669 | 1.895669 | 1.461300 | 1.385825 | -1.143269 | 0.669931 | -0.757478 | -1.227795 | 0.227342 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | 1.666108 | 1.666108 | 1.532931 | 1.473621 | -1.148881 | 0.822231 | -0.398544 | -0.335904 | 0.703216 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.511766 | 1.331711 | 1.511766 | 1.416321 | -1.067755 | 0.611539 | -0.284747 | -0.171244 | 0.601544 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | inf | 238.758406 | 237.840226 | inf | inf | 2730.096528 | 2728.831814 | 4589.313071 | 4566.236430 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.973235 | 1.511850 | 1.973235 | 1.613324 | -0.857397 | 1.225660 | -0.345117 | -0.670859 | -0.115464 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.803647 | 1.803647 | 1.238969 | -0.722851 | 1.637512 | -0.308176 | 1.051709 | -0.064354 | -0.744491 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 1.855521 | 1.855521 | 1.315958 | -0.706278 | 1.675523 | -0.822732 | 0.742214 | -0.178496 | -0.922747 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Shape | 2.133065 | 2.133065 | 1.538032 | -0.805840 | 1.640840 | -0.431909 | 0.923125 | 0.294476 | -0.004366 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.447912 | 1.333949 | 1.417755 | 1.447912 | -1.085154 | -0.081421 | -0.355512 | -1.942236 | -1.010282 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | nn Temporal Discontinuties | 14.006658 | 1.814030 | 1.556257 | -1.023002 | 1.595988 | 6.808308 | 0.654999 | 14.006658 | 0.614950 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | 1.534989 | 1.500301 | 1.534989 | -0.833124 | 1.336053 | -1.167339 | 0.238524 | 0.179973 | -0.619552 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Shape | 1.782731 | 1.782731 | 1.551550 | 1.414890 | -0.832248 | 0.941467 | -0.589018 | -0.745238 | -0.518754 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.470231 | 1.114408 | -0.176024 | 1.470231 | -0.839423 | 0.808179 | -0.438120 | -0.368120 | -0.428077 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 0.839678 | 0.677168 | 0.602346 | 0.839678 | -1.137902 | -0.878253 | -0.930533 | -0.281767 | -1.426429 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.785473 | 0.024241 | 0.822945 | -0.730061 | 1.785473 | -1.083848 | 1.195661 | 0.302942 | -0.365829 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.287751 | -0.155047 | 0.673381 | -1.154340 | 1.287751 | -1.439508 | 0.352244 | -1.506787 | 0.726614 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.384920 | 0.726490 | -0.141128 | 1.384920 | -1.029709 | 0.695672 | -1.397232 | -1.231275 | -0.288140 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.595547 | -0.074015 | 0.777718 | -0.915646 | 1.595547 | -1.100068 | 0.723953 | -0.174244 | -0.928032 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.295252 | 1.139508 | -0.072078 | 1.295252 | -1.051462 | 0.629719 | -1.384103 | -1.145565 | 0.064470 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 139 | N13 | RF_maintenance | ee Power | 1.467250 | -0.058542 | 0.909939 | -1.012742 | 1.467250 | -1.028725 | 0.912279 | -0.094504 | -0.712418 |